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Brown HG, Hanssen E. MeasureIce: accessible on-the-fly measurement of ice thickness in cryo-electron microscopy. Commun Biol 2022; 5:817. [PMID: 35965271 PMCID: PMC9376182 DOI: 10.1038/s42003-022-03698-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 07/11/2022] [Indexed: 11/12/2022] Open
Abstract
Ice thickness is arguably one of the most important factors limiting the resolution of protein structures determined by cryo-electron microscopy (cryo-EM). The amorphous atomic structure of the ice that stabilizes and protects biological samples in cryo-EM grids also imprints some additional noise in cryo-EM images. Ice that is too thick jeopardizes the success of particle picking and reconstruction of the biomolecule in the worst case and, at best, deteriorates eventual map resolution. Minimizing the thickness of the ice layer and thus the magnitude of its noise contribution is thus imperative in cryo-EM grid preparation. In this paper we introduce MeasureIce, a simple, easy to use ice thickness measurement tool for screening and selecting acquisition areas of cryo-EM grids. We show that it is possible to simulate thickness-image intensity look-up tables, also usable in SerialEM and Leginon, using elementary scattering physics and thereby adapt the tool to any microscope without time consuming experimental calibration. We benchmark our approach using two alternative techniques: the "ice channel" technique and tilt-series tomography. We also demonstrate the utility of ice thickness measurement for selecting holes in gold grids containing an Equine apoferritin sample, achieving a 1.88 Ångstrom resolution in subsequent refinement of the atomic map.
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Affiliation(s)
- Hamish G Brown
- Ian Holmes Imaging Center, Bio21 Molecular Science & Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia.
| | - Eric Hanssen
- Ian Holmes Imaging Center, Bio21 Molecular Science & Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia
- Department of Biochemistry and Pharmacology and ARC Industrial Transformation Training Center for Cryo-electron Microscopy of Membrane Proteins, The University of Melbourne, Parkville, Victoria, Australia
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Vilas JL, Carazo JM, Sorzano COS. Emerging Themes in CryoEM─Single Particle Analysis Image Processing. Chem Rev 2022; 122:13915-13951. [PMID: 35785962 PMCID: PMC9479088 DOI: 10.1021/acs.chemrev.1c00850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.
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Affiliation(s)
- Jose Luis Vilas
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - Jose Maria Carazo
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
| | - Carlos Oscar S Sorzano
- Biocomputing Unit, Centro Nacional de Biotecnologia (CNB-CSIC), Darwin, 3, Campus Universidad Autonoma, 28049 Cantoblanco, Madrid, Spain
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3
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Méndez J, Garduño E, Carazo JM, S Sorzano CO. Identification of incorrectly oriented particles in cryo-EM single particle analysis. J Struct Biol 2021; 213:107771. [PMID: 34324977 DOI: 10.1016/j.jsb.2021.107771] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/23/2021] [Accepted: 07/18/2021] [Indexed: 11/24/2022]
Abstract
The quality of a 3D map produced by the single-particle analysis method is highly dependent on an accurate assignment of orientations to the many experimental images. However, the problem's complexity implies the presence of several local minima in the optimized goal functions. Consequently, validation methods to confirm the angular assignment are very useful to yield higher-resolution 3D maps. In this work, we present a graph-signal-processing-based methodology that analyzes the correlation landscape as a function of the orientation, an approach allowing the estimation of the assigned orientations' reliability. Using this method, we may identify low-reliability images that probably incorrectly contribute to the final 3D reconstruction.
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Affiliation(s)
- Jeison Méndez
- Posgrado en Ingeniería Eléctrica, Universidad Nacional Autónoma de México, Cd.Universitaria, C.P.04510, Mexico City, Mexico.
| | - Edgar Garduño
- Department of Computer Science, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
| | - José María Carazo
- National Center of Biotechnology, CSIC, Campus Univ. Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain.
| | - Carlos Oscar S Sorzano
- Univ. San Pablo CEU, Campus Urb. Montepríncipe s/n, 28668, Boadilla del Monte, Madrid, Spain; National Center of Biotechnology, CSIC, Campus Univ. Autónoma de Madrid, 28049 Cantoblanco, Madrid, Spain.
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Ortiz S, Stanisic L, Rodriguez BA, Rampp M, Hummer G, Cossio P. Validation tests for cryo-EM maps using an independent particle set. J Struct Biol X 2020; 4:100032. [PMID: 32743544 PMCID: PMC7385033 DOI: 10.1016/j.yjsbx.2020.100032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by providing 3D density maps of biomolecules at near-atomic resolution. However, map validation is still an open issue. Despite several efforts from the community, it is possible to overfit 3D maps to noisy data. Here, we develop a novel methodology that uses a small independent particle set (not used during the 3D refinement) to validate the maps. The main idea is to monitor how the map probability evolves over the control set during the 3D refinement. The method is complementary to the gold-standard procedure, which generates two reconstructions at each iteration. We low-pass filter the two reconstructions for different frequency cutoffs, and we calculate the probability of each filtered map given the control set. For high-quality maps, the probability should increase as a function of the frequency cutoff and the refinement iteration. We also compute the similarity between the densities of probability distributions of the two reconstructions. As higher frequencies are included, the distributions become more dissimilar. We optimized the BioEM package to perform these calculations, and tested it over systems ranging from quality data to pure noise. Our results show that with our methodology, it possible to discriminate datasets that are constructed from noise particles. We conclude that validation against a control particle set provides a powerful tool to assess the quality of cryo-EM maps.
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Affiliation(s)
- Sebastian Ortiz
- Biophysics of Tropical Diseases, Max Planck Tandem Group, University of Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
| | - Luka Stanisic
- Max Planck Computing and Data Facility, 85748 Garching, Germany
| | - Boris A Rodriguez
- Grupo de Fósica Atómica y Molecular, Instituto de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
| | - Markus Rampp
- Max Planck Computing and Data Facility, 85748 Garching, Germany
| | - Gerhard Hummer
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany
- Institute of Biophysics, Goethe University, 60438 Frankfurt am Main, Germany
| | - Pilar Cossio
- Biophysics of Tropical Diseases, Max Planck Tandem Group, University of Antioquia UdeA, Calle 70 No. 52-21, Medellín, Colombia
- Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany
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Abstract
Cross-validation is used to determine the validity of a model on unseen data by assessing if the model is overfitted to noise. It is widely used in many fields, from artificial intelligence to structural biology in X-ray crystallography and nuclear magnetic resonance. Although there are concerns of map overfitting in cryo-electron microscopy (cryo-EM), cross-validation is rarely used. The problem is that establishing a performance metric of the maps over unseen data (given by 2D-projection images) is difficult due to the low signal-to-noise ratios in the individual particles. Here, I present recent advances for cryo-EM map reconstruction. I highlight that the gold-standard procedure can fail to detect map overfitting in certain cases, showing the necessity of assessing the map quality on unbiased data. Finally, I describe the challenges and advantages of developing a robust cross-validation methodology for cryo-EM.
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Affiliation(s)
- Pilar Cossio
- Biophysics of Tropical Diseases, Max Planck Tandem Group, University of Antioquia UdeA, Calle 70 No. 52-21, Medellin, Colombia.,Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany
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The first single particle analysis Map Challenge: A summary of the assessments. J Struct Biol 2018; 204:291-300. [PMID: 30114512 DOI: 10.1016/j.jsb.2018.08.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Revised: 08/03/2018] [Accepted: 08/11/2018] [Indexed: 12/13/2022]
Abstract
The recent successes of cryo-electron microscopy fostered great expectation of solving many new and previously recalcitrant biomolecular structures. However, it also brings with it the danger of compromising the validity of the outcomes if not done properly. The Map Challenge is a first step in assessing the state of the art and to shape future developments in data processing. The organizers presented seven cases for single particle reconstruction, and 27 members of the community responded with 66 submissions. Seven groups analyzed these submissions, resulting in several assessment reports, summarized here. We devised a range of analyses to evaluate the submitted maps, including visual impressions, Fourier shell correlation, pairwise similarity and interpretation through modeling. Unfortunately, we did not find strong trends. We ascribe this to the complexity of the challenge, dealing with multiple cases, software packages and processing approaches. This puts the user in the spotlight, where his/her choices becomes the determinant of map quality. The future focus should therefore be on promulgating best practices and encapsulating these in the software. Such practices include adherence to validation principles, most notably the processing of independent sets, proper resolution-limited alignment, appropriate masking and map sharpening. We consider the Map Challenge to be a highly valuable exercise that should be repeated frequently or on an ongoing basis.
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Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy. Nat Commun 2017; 8:629. [PMID: 28931821 PMCID: PMC5607000 DOI: 10.1038/s41467-017-00782-3] [Citation(s) in RCA: 132] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 07/27/2017] [Indexed: 11/29/2022] Open
Abstract
The orientation distribution of a single-particle electron cryomicroscopy specimen limits the resolution of the reconstructed density map. Here we define a statistical quantity, the efficiency, Eod, which characterises the orientation distribution via its corresponding point spread function. The efficiency measures the ability of the distribution to provide uniform information and resolution in all directions of the reconstruction, independent of other factors. This metric allows rapid and rigorous evaluation of specimen preparation methods, assisting structure determination to high resolution with minimal data. A number of parameters influence the resolution of a cryo-EM structure. Here the authors investigate the effects of specimen orientation in single particle cryo-EM and present open-source software for rapidly assessing orientation distributions to improve data collection.
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